{"id":"W2463063833","doi":"10.2196/mhealth.5637","title":"Reciprocal Reinforcement Between Wearable Activity Trackers and Social Network Services in Influencing Physical Activity Behaviors","year":2016,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Activity tracker; Wearable computer; Reciprocal; Physical activity; Wearable technology; Reinforcement; Human–computer interaction; Computer science; mHealth; Social network (sociolinguistics); Psychology; Applied psychology; Internet privacy; Social psychology; Physical medicine and rehabilitation; World Wide Web; Medicine; Social media; Psychological intervention","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005385913,0.0002950764,0.0002391917,0.0007707917,0.001075435,0.001473575,0.000420242,0.0004303538,0.003100355],"category_scores_gemma":[0.01684861,0.0002025861,0.0004650065,0.0004815409,0.0008905021,0.001011865,0.00253298,0.0006285755,0.0002527859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008206528,"about_ca_system_score_gemma":0.001462648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002307466,"about_ca_topic_score_gemma":0.004031231,"domain_scores_codex":[0.9930958,0.005528338,0.0001740583,0.0004110673,0.0004747165,0.0003160515],"domain_scores_gemma":[0.9867605,0.009851496,0.001275464,0.0004469426,0.0006595337,0.001005966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008546506,0.002402864,0.5201514,0.001873195,0.0004863772,0.001023097,0.05947781,0.001067344,0.004603731,0.005035555,0.001966071,0.4010578],"study_design_scores_gemma":[0.0003495208,0.005742898,0.8593257,0.002217986,0.001402447,0.001794193,0.06893115,0.01072301,0.004002845,0.007871223,0.03752002,0.000118838],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745544,0.00122322,0.003793539,0.001137133,0.0000816598,0.0002809109,0.0000602429,0.00005658778,0.01881221],"genre_scores_gemma":[0.9968932,0.0003538134,0.002105387,0.00008783792,0.00001573232,0.0001137787,0.00001116071,0.000005272397,0.0004139597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005385913,"threshold_uncertainty_score":0.02848381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06697557158583003,"score_gpt":0.446960945398875,"score_spread":0.379985373813045,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}